Resumen: Objectives
To critically identify studies that evaluate the effects of cueing in virtual motor rehabilitation in patients having different neurological disorders and to make recommendations for future studies.
Methods
Data from MEDLINE®, IEEExplore, Science Direct, Cochrane library and Web of Science was searched until February 2015. We included studies that investigate the effects of cueing in virtual motor rehabilitation related to interventions for upper or lower extremities using auditory, visual, and tactile cues on motor performance in non-immersive, semi-immersive, or fully immersive virtual environments. These studies compared virtual cueing with an alternative or no intervention.
Results
Ten studies with a total number of 153 patients were included in the review. All of them refer to the impact of cueing in virtual motor rehabilitation, regardless of the pathological condition. After selecting the articles, the following variables were extracted: year of publication, sample size, study design, type of cueing, intervention procedures, outcome measures, and main findings. The outcome evaluation was done at baseline and end of the treatment in most of the studies. All of studies except one showed improvements in some or all outcomes after intervention, or, in some cases, in favor of the virtual rehabilitation group compared to the control group.
Conclusions
Virtual cueing seems to be a promising approach to improve motor learning, providing a channel for non-pharmacological therapeutic intervention in different neurological disorders. However, further studies using larger and more homogeneous groups of patients are required to confirm these findings. Idioma: Inglés DOI: 10.1016/j.jbi.2016.01.006 Año: 2016 Publicado en: JOURNAL OF BIOMEDICAL INFORMATICS 60 (2016), 49-57 ISSN: 1532-0464 Factor impacto JCR: 2.753 (2016) Categ. JCR: COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS rank: 25 / 105 = 0.238 (2016) - Q1 - T1 Categ. JCR: MEDICAL INFORMATICS rank: 7 / 23 = 0.304 (2016) - Q2 - T1 Factor impacto SCIMAGO: 0.856 - Health Informatics (Q1) - Computer Science Applications (Q1)